class_docstr: Aggregate the global object representation to update the representation for each pixel.
code: def __init__(
      self, in_channels, key_channels, out_channels, dropout_rate=0.1
  ):
      super().__init__()
  
      self.attention_block = ObjectAttentionBlock(
          in_channels, key_channels
      )
      self.conv1x1 = nn.Sequential(
          layers.ConvBNReLU(
              2 * in_channels, out_channels, 1, bias_attr=False
          ),
          nn.Dropout2D(dropout_rate),
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
label_desc: Use image node_id 1 to create a new SpatialOCRModule object from inherited base classes: nn with example: obj = SpatialOCRModule(in_channels, key_channels, out_channels, dropout_rate)